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Abstract

Background:The New England Journal of Medicine reports that 1 in 5 discharged Medicare patients is readmitted to a hospital within 30 days. Readmissions are costly to hospitals and are a major disruption to a patient’s life, creating financial and emotional strain. Project Re-Engineered Discharge (RED), a nationally recognized program to reduce preventable hospital readmissions, was implemented at Sutter Health’s California Pacific Medical Center (CPMC) beginning in late 2013. The most challenging of the 12 components of the intervention is the coordination and timely completion of follow-up care with a primary care physician after hospital discharge.

Methods: To ensure that each patient going home from the hospital would have a post-acute care appointment scheduled, we developed Discharge Planner, a web-based software application to support the required multistep, multidisciplinary workflow. We then piloted the tool in a single unit at CPMC. We measured fidelity by monitoring whether case managers were launching the application and recorded the proportion of patients with appointments scheduled at the time of discharge. We used patient electronic health records to measure the proportion of patients who attended follow-up appointments postdischarge. Finally, we used provider surveys to determine user acceptability.

Results: The app was opened an average of 40 times/day for a single hospital unit during business hours and < 5 times/day on weekends. Follow-up appointment scheduling increased from < 20% during the 4 months “pre-go-live” to > 50% during the 5-month “post-go-live” period. Only 20%–30% of patients kept their scheduled appointments throughout the study period, with no change during the “post-go-live” period. User acceptance scores were highly favorable (on a scale from 1 to 100, average scores were 73 overall and 87 among those case managers who rely most heavily on the application).

Conclusion: The application was highly successful at accomplishing its primary goal, scheduling follow-up appointments, and it has been accepted into the workflow. However, patients still do not appear to be keeping their follow-up appointments. Our next step is to uncover strategies to better measure kept appointments and to identify factors that prevent patients from keeping their appointments.